Did you know that Earth Day, a holiday that raises awareness of environmental issues such as pollution and deforestation, was first celebrated in 1970? And that it is now recognized in more than 192 countries?
The annual Earth Day occurs this week and with it as a reminder, it is an appropriate time to consider the impact your business and supply chain has on the environment and how analytics and AI can help reduce your carbon footprint.
Decarbonization is a focus area for many organizations, and companies have begun rolling out solutions such as solar panels for clean energy production. However, one study revealed that companies’ supply chains generate 11.4 times the emissions than in-house operations.
Inefficient supply chains are bad for the environment and bad for your business. Typical supply chains can take a toll on the environment in the following ways: resource extraction and processing, transportation and logistics, manufacturing and production, and waste generation.
To improve the traditional approach, LRS suggests you use your data and AI to optimize your supply chain and mitigate environmental impact in these areas:
Demand forecasting: Reduce overproduction and waste.
AI algorithms are extremely accurate in predicting consumer demand when given historical market and trend data. By accurately forecasting demand, you can right-size your inventory without overproducing, thus minimizing waste. A more streamlined supply chain means lower impact on the environment and better management of resources.
Route optimization: Minimize transportation emissions.
According to a UN report, the transportation and logistics industry is responsible for 25% of global greenhouse gas emissions. Using electric vehicles with zero emissions is an obvious part of the solution, but AI allows organizations to improve the transportation aspect of supply chains. By analyzing real-time traffic, weather, fuel price, and fuel efficiency data, AI can optimize delivery routes. Using AI for route optimization not only reduces your carbon footprint but leads to a cost savings.
Improved Quality Control: Eliminate production waste.
Wouldn’t it be helpful to identify manufacturing defects and deviations in real-time? By discovering and mitigating quality issues faster, you can reduce the production of defective products, thereby reducing the generation of waste. Catching defective products earlier guarantees your resources are used more efficiently and reduces ecological footprint by reducing your need for raw materials.
Sustainable sourcing: Identify eco-friendly materials and suppliers.
AI can be used to examine data about all partners in your supply chain and how they comply with environmental regulations, use energy, produce waste, and consume water. IoT and Blockchain, along with AI, allow you to monitor and verify the responsible origin of raw materials and ensure you are collaborating with suppliers who prioritize environmental sustainability.
Resource management: Optimize energy consumption.
By proactively monitoring energy and water consumption, you demonstrate your commitment to environmental responsibility. AI applications are helping companies find areas of inefficiency by analyzing IoT sensor and smart meter information for electricity and water consumption.
Challenges such as data accessibility and integration persist, but AI is supercharging sustainable supply chains. By using AI to make forecasting more accurate, optimize routes, track resource usage, and monitor product quality, you can improve your organization’s own productivity and profitability, while contributing to a greener future for everyone.
If you are interested in implementing AI solutions in these or additional areas of your organization, please contact us to request a meeting with LRS. Don’t have an information architecture you trust yet? LRS can also help you collect, organize, and analyze your data so that it is business ready.